Volume 18 | Issue 4
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The analysis includes suppliers, manufacturing, warehousing, and distribution. In fact, a number of Fortune 100 companies require such analysis before approving capital to add manufacturing or warehousing infrastructure. Those on the cutting edge regularly use SCND analysis to understand the true delivered cost to supply each customer as well as the price required from the customer to achieve profitability goals. Advances in network design modelling and optimization have also enabled broader analyses that focus on the competitors’ collective supply chains, which in turn show how best to compete in the market to maximize profits.
Historical context
Twenty-five years ago, the tools to analyze and create an optimized supply chain infrastructure were new and untested. Back then, leading-edge companies employed this technology to gain a competitive advantage. They analyzed the trade-offs among the different supply chain expenses (i.e. raw material, production, transportation, distribution and inventory) against their ability to meet customer demand at higher customer service levels.
What was once the domain of a few has become business as usual for supply chain management teams. While the entire business community has yet to catch up to thought leaders using SCND, those who have embraced the concept hope to forge ahead in their markets.
Supply chain managers that are on the bandwagon perform some sort of optimization-based supply chain analysis when performing these key functions:
Sustained Supply Chain Network Design
Because it is often difficult to assemble the data required to perform the analysis, some companies are tempted to “get it done so we can move on,” which prevents them from assessing ongoing risks and opportunities. For the best results, an SCND analysis should be performed at regular intervals. Higher performing businesses create sustainable corporate processes to capture relevant data so they may easily reassess their supply chain network structure and operations.
Relevant data also needs to be good data, as this is the only type of data that can drive effective supply chain analysis. Many companies struggle with understanding the true activity costs associated with one or more of the following: raw materials supply, production, packaging, warehousing, distribution and inventory—because the data is outdated or in question. When running a significant supply chain analysis and design project, SCND analysts often spend the bulk of time and effort gathering, organizing and validating the input data that drive the analysis. Newly developed procedures can reduce if not eliminate this wasted time and effort altogether.
The companies that implement best practices expand data collection warehouses to include the key activity-based operations and cost data that are used in their strategic and tactical network optimization analyses. The data is kept relevant and current through the use of systematic data management tools, so that it is instantly available for timely what-if scenarios. These what-if scenarios might include:
Companies that maintain accurate, current data and do not have to start from scratch on each new what-if analysis can respond quickly and appropriately to opportunities that present themselves.
Extending Supply Chain Network
Design to Competitive Markets If a company has used optimization SCND to analyze a portion of its business in the past couple of years, it is running with the herd. If a company has implemented a sustainable business process to refresh and maintain the critical data and is able to run supply chain network what-if analysis at a moment’s notice, the company is slightly ahead of most of the competition. Those entities that use SCND analysis to understand the true delivered cost of supplying product to each customer and manage their business accordingly are the real leaders.
Advances in network design modeling, optimization, and game theory have recently opened the door to a broader analysis that focuses on the collective supply chains of all competitors in a marketplace. These tools can be used to discover and predict which customer/product/price point combinations will maximize profit. There are three key steps required to accomplish this goal:
1. Understand the total delivered cost to each customer:
Understanding the true total delivered cost to each customer lets the
company analyze and determine the profit being earned from each
account. It also partially impacts pricing decisions, especially in
competitive situations or when the demand is greater than the company’s
ability to supply. Not only does this analysis determine the profitability by
customer, it also assesses the impact of adding or dropping an account,
thus answering the question, “Even though it’s low margin business, can
we afford to lose the volume?”
2. Estimate competitor costs for supplying to a shared set of
customers:
While pricing information is largely influenced by the internal costs for
producing, delivering and selling to customers, it is also heavily influenced
by the market conditions and the competition’s marketplace realities. To
understand the market dynamics, companies need to be able to reasonably
estimate competitors’ costs. For example, for companies that are in an
industry where transportation delivery costs are significant, regionally
located manufacturing will have an impact on price and profitability.
Understanding which customers are more profitable and, at the same time,
knowing which are more costly for competitors to serve helps develop a
winning strategy.
3. Use cutting edge optimization technology to model the competitive
market:
While most businesses are good at determining pricing and identifying
profitable customers intuitively and on and ad hoc basis, few have put into
place the rigorous business processes and analytics to be able to do it
accurately and consistently. This requires a deep understanding of a
company’s total delivered cost, its supply chain sourcing options, and the
flexibility a company has on both the cost and revenue side of the
equation. It also requires a better understanding of the competition’s
supply chain economics, and what they may or may not be able to do
based on their costs.
Add Profit to the Bottom Line
Supply chain network design optimization tools have become well integrated into modern business decision-making processes at leading edge companies. The tools are used to rigorously analyze and make the best decisions in response to both short-term events such as weather disruptions, spot sales opportunities, utility outages and to longer-term strategy issues, such as capacity expansion or mergers and acquisitions. These analytical approaches and technologies can be game changers. The newest versions of SCND tools have been expanded: businesses can now analyze not just their own operations, but also the sum of multiple supply chains in the competitive marketplace, which can be a boon to the bottom line.
Alan Kosansky and Ted Schaefer are are senior members of the management team for Profit Point.
Profit Point is a global leader in supply chain optimization systems. The
company provides such services as infrastructure and supply chain planning,
scheduling, distribution and warehouse utilization improvement. For more
information, please call (610) 645-5557 or visit www.profitpt.com.
Tune in to hear from Chris Brown, Vice President of Sales at CADDi, a leading manufacturing solutions provider. We delve into Chris’ role of expanding the reach of CADDi Drawer which uses advanced AI to centralize and analyze essential production data to help manufacturers improve efficiency and quality.